Create iwslt14.py

iwslt14.py

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+# coding=utf-8
+"""The IWSLT 2014 Evaluation Campaign includes a multilingual TED Talks MT task."""
+
+import datasets
+
+from bs4 import BeautifulSoup
+from pathlib import Path
+
+_CITATION = """\
+@inproceedings{cettoloEtAl:EAMT2012,
+Address = {Trento, Italy},
+Author = {Mauro Cettolo and Christian Girardi and Marcello Federico},
+Booktitle = {Proceedings of the 16$^{th}$ Conference of the European Association for Machine Translation (EAMT)},
+Date = {28-30},
+Month = {May},
+Pages = {261--268},
+Title = {WIT$^3$: Web Inventory of Transcribed and Translated Talks},
+Year = {2012}}
+"""
+
+_DESCRIPTION = """\
+The IWSLT 2014 Evaluation Campaign includes the MT track on TED Talks. In this edition, the official language pairs are five:
+
+  from English to French
+  from English to German
+  from German to English
+  from English to Italian
+  from Italian to English
+
+Optional tasks are proposed with English paired in both directions with other twelve languages:
+
+  from/to English to/from Arabic, Spanish, Farsi, Hebrew, Dutch, Polish, Portuguese-Brazil, Romanian, Russian, Slovenian, Turkish and Chinese
+
+Submitted runs on additional pairs will be evaluated as well, in the hope to stimulate the MT community to evaluate systems on common benchmarks and to share achievements on challenging translation tasks.
+"""
+
+_URL = "https://drive.google.com/file/d/1GnBarJIbNgEIIDvUyKDtLmv35Qcxg6Ed/view"
+
+_HOMEPAGE = "https://wit3.fbk.eu/2014-01"
+
+_LANGUAGES = ["ar", "de", "es", "fa", "he", "it", "nl", "pl", "pt-br", "ro", "ru", "sl", "tr", "zh"]
+_PAIRS = [(lang, "en") for lang in _LANGUAGES] + [("en", lang) for lang in _LANGUAGES]
+
+
+class IWSLT14Config(datasets.BuilderConfig):
+    """BuilderConfig for IWSLT14 Dataset"""
+
+    def __init__(self, language_pair=(None, None), **kwargs):
+        """
+
+        Args:
+            language_pair: the language pair to consider. Should
+            contain 2-letter coded strings. For example: ("ja", "en").
+            **kwargs: keyword arguments forwarded to super.
+        """
+        super(IWSLT14Config, self).__init__(
+            name="%s-%s" % (language_pair[0], language_pair[1]),
+            description="IWSLT 2014 multilingual dataset.",
+            version=datasets.Version("1.0.0", ""),
+            **kwargs,
+        )
+
+        # Validate language pair.
+        assert language_pair in _PAIRS
+
+        self.language_pair = language_pair
+
+
+class IWSLT14(datasets.GeneratorBasedBuilder):
+    """The IWSLT 2014 Evaluation Campaign includes a multilingual TED Talks MT task."""
+
+    BUILDER_CONFIGS = [IWSLT14Config(language_pair=pair) for pair in _PAIRS]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # datasets.features.FeatureConnectors
+            features=datasets.Features(
+                {
+                    "id": datasets.features.Value(dtype='string', id=None),
+                    "translation": datasets.features.Translation(languages=self.config.language_pair),
+                }
+            ),
+            # If there's a common (input, target) tuple from the features,
+            # specify them here. They'll be used if as_supervised=True in
+            # builder.as_dataset.
+            supervised_keys=None,
+            # Homepage of the dataset for documentation
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+
+        def _get_drive_url(url):
+            return f"https://drive.google.com/uc?id={url.split('/')[5]}"
+
+        source, target = self.config.language_pair
+        pair = f"{source}-{target}"
+        ex_dir = dl_manager.download_and_extract(_get_drive_url(_URL))
+        dl_dir = dl_manager.extract(f"{ex_dir}/2014-01/texts/{source}/{target}/{pair}.tgz")
+        path_tmpl = f"{dl_dir}/{pair}/IWSLT14.%s.{pair}.%s.xml"
+        subsets = {
+            "dev": ["TED.dev2010", "TEDX.dev2012"],
+            "test": ["TED.tst2010", "TED.tst2011", "TED.tst2012"],
+        }
+        files = {
+            "train": {
+                "source_files": [f"{dl_dir}/{pair}/train.tags.{pair}.{source}"],
+                "target_files": [f"{dl_dir}/{pair}/train.tags.{pair}.{target}"],
+                "split": "train",
+            },
+            "dev": {
+                "source_files": [path_tmpl % (year, source) for year in subsets["dev"]],
+                "target_files": [path_tmpl % (year, target) for year in subsets["dev"]],
+                "split": "validation",
+            },
+            "test": {
+                "source_files": [path_tmpl % (year, source) for year in subsets["test"]],
+                "target_files": [path_tmpl % (year, target) for year in subsets["test"]],
+                "split": "test",
+            },
+        }
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs=files["train"]),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs=files["dev"]),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs=files["test"]),
+        ]
+
+    def _generate_examples(self, source_files, target_files, split):
+        """Yields examples."""
+        source, target = self.config.language_pair
+
+        def _parse_doc(file_path: str):
+            html_doc = Path(file_path).read_text()
+            html_doc = ''.join([f'<seg>{line}</seg>' if not line.startswith('<') else line
+                                for line in html_doc.splitlines()])
+            soup = BeautifulSoup(html_doc, features="lxml")
+            docs = {}
+            docid = 0
+            for url in soup.find_all('url'):
+                docid += 1
+                s = url
+                segid = 0
+                while s.next_sibling and s.next_sibling.name == 'seg':
+                    segid += 1
+                    docs[f'docid-{docid}_segid-{segid}'] = s.next_sibling.text.strip()
+                    s = s.next_sibling
+            return docs
+
+        def _parse_xml(file_path: str):
+            html_doc = Path(file_path).read_text()
+            soup = BeautifulSoup(html_doc, features="lxml")
+            docs = {}
+            for doc in soup.find_all('doc'):
+                docid = doc.attrs['docid']
+                for title in doc.find_all('title'):
+                    docs[f'docid-{docid}_title'] = title.text.strip()
+                for desc in doc.find_all('description'):
+                    docs[f'docid-{docid}_desc'] = desc.text.strip()
+                for seg in doc.find_all('seg'):
+                    segid = seg.attrs['id']
+                    docs[f'docid-{docid}_segid-{segid}'] = seg.text.strip()
+            return docs
+
+        def _parse(file_path: str):
+            if file_path.endswith('.xml'):
+                return _parse_xml(file_path)
+            else:
+                return _parse_doc(file_path)
+
+        id_ = 0
+        seg_counter = 0
+        doc_counter = 10000
+        talk_id = f"d{doc_counter}"
+        flag = ""
+        for source_file, target_file in zip(source_files, target_files):
+            src = _parse(source_file)
+            trg = _parse(target_file)
+
+            for k, src_sent in src.items():
+                if k in trg:
+                    trg_sent = trg[k]
+
+                    yield id_, {
+                        "id": k,
+                        "translation": {source: src_sent, target: trg_sent}
+                    }
+                    id_ += 1